TY - GEN
T1 - Robust multivariate methods for the analysis of the university performance
AU - Bini, Matilde
N1 - Publisher Copyright:
© 2005, Springer-Verlag. Heidelberg 2005.
PY - 2005/1/1
Y1 - 2005/1/1
N2 - One of the most important problems among the methodological issues discussed in cluster analysis is the identification of the correct number of clusters and the correct allocation of units to their natural clusters. In this paper we use the forward search algorithm, recently proposed by Atkinson, Riani and Cerioli (2004) to scrutinize in a robust and efficient way the output of k-means clustering algorithm. The method is applied to a data set containing efficiency and effectiveness indicators, collected by the National University Evaluation Committee (NUEC), used to evaluate the performance of Italian universities.
AB - One of the most important problems among the methodological issues discussed in cluster analysis is the identification of the correct number of clusters and the correct allocation of units to their natural clusters. In this paper we use the forward search algorithm, recently proposed by Atkinson, Riani and Cerioli (2004) to scrutinize in a robust and efficient way the output of k-means clustering algorithm. The method is applied to a data set containing efficiency and effectiveness indicators, collected by the National University Evaluation Committee (NUEC), used to evaluate the performance of Italian universities.
UR - http://www.scopus.com/inward/record.url?scp=85042934214&partnerID=8YFLogxK
U2 - 10.1007/3-540-27373-5_34
DO - 10.1007/3-540-27373-5_34
M3 - Contribución a la conferencia
AN - SCOPUS:85042934214
SN - 9783319557076
SN - 9783319557229
SN - 9783540238096
T3 - Studies in Classification, Data Analysis, and Knowledge Organization
SP - 285
EP - 292
BT - Studies in Classification, Data Analysis, and Knowledge Organization
A2 - Vichi, Maurizio
A2 - Monari, Paola
A2 - Mignani, Stefania
A2 - Montanari, Angela
PB - Springer Science and Business Media Deutschland GmbH
T2 - Biannual meeting of the Classification and Data Analysis Group of the Italian Statistical Society, CLADAG 2003
Y2 - 22 September 2003 through 24 September 2003
ER -